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MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis
v1v2v3v4 (latest)

MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis

15 November 2017
Rushil Anirudh
Jayaraman J. Thiagarajan
R. Sridhar
T. Bremer
    FAttAAML
ArXiv (abs)PDFHTML

Papers citing "MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis"

7 / 7 papers shown
Title
Explaining Latent Representations with a Corpus of Examples
Explaining Latent Representations with a Corpus of Examples
Jonathan Crabbé
Zhaozhi Qian
F. Imrie
M. Schaar
FAtt
84
38
0
28 Oct 2021
Graphs as Tools to Improve Deep Learning Methods
Graphs as Tools to Improve Deep Learning Methods
Carlos Lassance
Myriam Bontonou
Mounia Hamidouche
Bastien Pasdeloup
Lucas Drumetz
Vincent Gripon
GNNAI4CEAAML
87
0
0
08 Oct 2021
Graph signal processing for machine learning: A review and new
  perspectives
Graph signal processing for machine learning: A review and new perspectives
Xiaowen Dong
D. Thanou
Laura Toni
M. Bronstein
P. Frossard
94
168
0
31 Jul 2020
Deep geometric knowledge distillation with graphs
Deep geometric knowledge distillation with graphs
Carlos Lassance
Myriam Bontonou
G. B. Hacene
Vincent Gripon
Jian Tang
Antonio Ortega
56
39
0
08 Nov 2019
Improved Visual Localization via Graph Smoothing
Improved Visual Localization via Graph Smoothing
Carlos Lassance
Yasir Latif
Ravi Garg
Vincent Gripon
Ian Reid
50
2
0
07 Nov 2019
Shapley Homology: Topological Analysis of Sample Influence for Neural
  Networks
Shapley Homology: Topological Analysis of Sample Influence for Neural Networks
Kaixuan Zhang
Qinglong Wang
Xue Liu
C. Lee Giles
TDI
33
3
0
15 Oct 2019
Introducing Graph Smoothness Loss for Training Deep Learning
  Architectures
Introducing Graph Smoothness Loss for Training Deep Learning Architectures
Myriam Bontonou
Carlos Lassance
G. B. Hacene
Vincent Gripon
Jian Tang
Antonio Ortega
59
18
0
01 May 2019
1